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phenobase
/
phenovisionL

Image Classification
Transformers
Safetensors
English
vit
vision
biology
ecology
phenology
plants
plant-phenology
leaf-phenology
iNaturalist
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use phenobase/phenovisionL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use phenobase/phenovisionL with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="phenobase/phenovisionL")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("phenobase/phenovisionL")
    model = AutoModelForImageClassification.from_pretrained("phenobase/phenovisionL")
  • Notebooks
  • Google Colab
  • Kaggle
phenovisionL
1.21 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
rdinnager's picture
rdinnager
Add family-level accuracy statistics
dfac208 verified 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    10.8 kB
    Update model card with complete documentation 2 months ago
  • config.json
    718 Bytes
    Upload ViTForImageClassification 11 months ago
  • epoch_1_threshold_buffers.csv
    181 Bytes
    Add threshold buffer parameters 2 months ago
  • family_stats.csv
    8.44 kB
    Add family-level accuracy statistics 2 months ago
  • model.safetensors
    1.21 GB
    xet
    Upload ViTForImageClassification 11 months ago